Probabilistic learning on manifolds (PLoM) with partition

The probabilistic learning on manifolds (PLoM) introduced in 2016 has solved difficult supervised problems for the “small data” limit where the number N of points in the training set is small. Many extensions have since been proposed, making it possible to deal with increasingly complex cases. However, the performance limit has been observed and explained for applications for which N is very small and for which the dimension of the diffusion-map basis is close to N. For these cases, we propose a novel extension based on the introduction of a partition in independent random vectors. We take advantage of this development to present improvements of the PLoM such as a simplified algorithm for constructing the diffusion-map basis and a new mathematical result for quantifying the concentration of the probability measure in terms of a probability upper bound. The analysis of the efficiency of this extension is presented through two applications.     

分布式多元随机动态场景生成及快速精准场景降维算法

高比例新能源及多源耦合是电力系统发展的重要特征,这也为系统稳定经济运行提出了新挑战。该文以园区型多能系统为对象,研究了分布式多元随机动态场景分析,从多时空角度有效量化不确定因素给系统造成的影响,可为系统灵活重构、多维度协同运行与决策提供有力模型与场景支撑。首先由预测误差驱动拟合多元功率预测误差概率分布,全面反映随机功率出力信息,提高模型泛化性;以时序相关范围参数为数据驱动关联变量,高效动态控制波动强度;最终场景生成利用逆变换映射思想保证置信度。然后针对典型场景提取,提出一种综合递归聚类思想的多段嵌套削减算法,结合改进Wasserstein距离指标,兼具准确、时效、稳定方面的优势。最后由对比实验论证该方法的前沿有效性。     

无线电综合测试仪校准装置的研究及其不确定度分析

This calibration device of radio comprehensive tester is studied and established in this paper. It solves the verification and calibration of a large number of general-purpose radio comprehensive testers. The calibration device consists of four calibration sub- systems and calibration software system, including RF generator, audio generator, audio analyzer and RF analyzer. It also researches on the configuration of standard equipment and analyzes the uncertainty of the calibration devices, ensuring accurate and reliable val- ue transfer.     

大坝服役非概率可靠性分析方法

针对大坝服役可靠性影响因子具有非概率不确定特征的情况,建立了定量刻画大坝服役可靠性非概率影响因子的Info-gap模型,运用Info-gap决策理论和体积比非概率可靠性度量方法,提出了大坝服役非概率可靠性分析方法,拟定了大坝服役非概率目标可靠度。应用提出的非概率方法分析了某大坝结构服役可靠性,各功能模式可靠性分析结果说明了该方法的工程适用性,同时也验证了所拟定大坝服役非概率目标可靠度的合理性。     

Data quality and uncertainty assessment methodology for pavement LCA

In performing pavement life cycle assessment (LCA), users are facing various reports of energy intensity coefficient (EIC) of pavement materials which differ considerably among data sources and therefore alter the LCA results significantly. Instead of selecting a certain EIC without or of little explanation for the current pavement LCA practices, this study proposed a methodology to build probability density function (PDF) for EIC based on available data-set and their qualities. Each data was first evaluated about the data quality indicator (DQI) through data quality pedigree matrix and converted to PDF in modified Beta distribution form. Three weighting methods, the DQI one, coefficient of variation (COV) one and analytical hierarchy process (AHP) one, were developed to assign weightings for different data. Monte Carlo simulation was run with the weighted PDF of each data as input to obtain the ultimate PDF for EIC. A case study to estimate the bitumen’s EIC with eight data samples were performed using the proposed methodology. It is found (1): the estimates by the proposed methodology is of higher reliability (lower COV) compared to any single data due to utilisation of information of the overall data samples; (2) the AHP weighting method is most favoured despite the results of the three weighting methods are close; (3) the central estimates of bitumen’s EIC are between5.4~5.8 MJ/kg. The proposed methodology is helpful in aiding calculating EICs for pavement materials and capturing uncertainties in LCA results in a statistical sense.     

计及时间相关性的微能源网鲁棒规划方法

微能源网以能源的梯级利用为原则,可实现风、光等多种新能源的高比例消纳,满足区域内电、热、冷等多种能源需求。微能源网中存在新能源出力与冷、热、电负荷的多重不确定性。为增强系统规划结果的鲁棒性,常采用不确定集表述新能源出力与多种用能需求的不确定性,实现针对微能源网的鲁棒规划设计,往往使系统规划结果过于保守,降低系统经济性。为克服以上问题,规避实际运行中不可能发生的场景,降低系统规划结果的保守性,文章提出一种考虑时间相关性的微能源网鲁棒规划模型。该模型在计及多重源荷不确定性的基础上,进一步考虑新能源出力与冷、热、电负荷的时间相关性。通过算例对传统不确定集与所提出的改进不确定集进行对比分析,验证了所提模型及方法的优越性和有效性。     

Supply chain network design under the risk of uncertain disruptions

Facility disruptions in the supply chain often lead to catastrophic consequences, although they occur rarely. The low frequency and non-repeatability of disruptive events also make it impossible to estimate the disruption probability accurately. Therefore, we construct an uncertain programming model to design the three-echelon supply chain network with the disruption risk, in which disruptions are considered as uncertain events. Under the constraint of satisfying customer demands, the model optimises the selection of retailers with uncertain disruptions and the assignment of customers and retailers, in order to minimise the expected total cost of network design. In addition, we simplify the proposed model by analysing its properties and further linearise the simplified model. A Lagrangian relaxation algorithm for the linearised model and a genetic algorithm for the simplified model are developed to solve medium-scale problems and large-scale problems, respectively. Finally, we illustrate the effectiveness of proposed models and algorithms through several numerical examples.     

分光光度法测定火腿肠中亚硝酸盐含量的不确定度评定

目的根据JJF1059.1-2012《测定不确定度的评定与表示》和GB 5009.33-2016《食品安全国家标准食品中亚硝酸盐与硝酸盐的测定》测定火腿肠中亚硝酸盐含量并进行不确定度评定。方法利用分光光度法测定火腿肠中亚硝酸盐含量,并建立相应的数学模型对测定过程中的称量、定容、分取、稀释、测定等引入的不确定度来源及其分量进行系统的分析。结果火腿肠中亚硝酸盐含量为4.31mg/kg,置信概率为95%时,最终得到测量的扩展不确定度为0.138 mg/kg (k=2)。结论火腿肠亚硝酸盐测定过程中最主要的不确定度来源为最小二乘法拟合的曲线,可通过减小标准品称量、定容等操作误差对曲线绘制的影响,进而有效降低最终检测结果的扩展不确定度。     

电感耦合等离子体质谱法测定辣椒镉含量中不确定度的评估

摘要：目的 采用电感耦合等离子体质谱法(ICP-MS)测定辣椒中镉（Cd）含量，及评估测定过程产生的不确定度，以提高定量分析结果的可靠性。方法 建立数学模型，分析识别试样称量、试样定容、标准物质、标准溶液的配制、标准曲线的拟合、重复测量、回收试验等不确定度来源，量化各不确定度分量，计算合成标准不确定度。结果 辣椒中镉含量不确定度测定结果为：。结论 测定过程不确定度主要来源于标准溶液配制和标准曲线拟合。电感耦合等离子体质谱法测定辣椒中镉含量准确度高，重复性好，建立的不确定度评估能保证分析结果的质量。